This FIRST award application proposes to quantitatively analyze ethnographic data. The goal of this study is to develop guidelines for field researchers designing longitudinal studies of drugs and crime. This study will make use of two major ethnographic data bases, including a sample of male drug users and a sample of female drug users, to investigate methodological issues in field research on drug use, crime, and violence. Comparisons will be made between life history reports (retrospective) and weekly interview data on measures of drug use, crime, and violence in order to facilitate conclusions about the utility of retrospectively provided information about "typical" behavior. Analyses of trends in weekly reporting on a range of measures, including drug use, crime, and income variables will be carried out. Further conclusions about the comparability of retrospective and weekly reports will be drawn from comparisons of factor analyses constructed from variables obtained at different phases of the interview process. Comparisons between measures obtained at different intervals will facilitate conclusions about the appropriate number and spacing of interviews and about the reliability of alternative indices of drug use and criminal behavior. Alternative causal models will be constructed to study the association between drugs, crime, and violence. The role of life history and weekly interview data will be compared in these models. Portions of interviews from subjects who did not complete the study will be coded. Comparisons between non-completers and completers and between non-completers who dropped out early and late will be used to make suggestions about the future design of field research. All analyses will be stratified by sample, thus facilitating comparisons between men and women. Although the research will mainly be data analytic in nature, interpretations of analyses will be informed by ethnographic accounts contained in subject files. The principal investigator will work collaboratively with the ethnographers who collected the data.